Triple
T876558
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Belém |
E18930
|
entity |
| Predicate | knownFor |
P22
|
FINISHED |
| Object | Belém Tower |
E18926
|
NE FINISHED |
How this triple was built (2 steps)
Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.
NER
Named-entity recognition
gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: Belém Tower | Statement: [Belém, knownFor, Belém Tower]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Belém Tower Context triple: [Belém, knownFor, Belém Tower]
-
A.
Belém Tower
chosen
Belém Tower is a 16th-century fortified tower in Lisbon, Portugal, and a UNESCO World Heritage Site renowned as a symbol of the Age of Discoveries.
-
B.
Belém Palace
Belém Palace is the official residence of the President of Portugal, located in Lisbon’s Belém district and serving as a central site of Portuguese political and ceremonial life.
-
C.
Torre do Pinhão
Torre do Pinhão is a civil parish in the municipality of Sabrosa, located in Portugal’s Douro wine region.
-
D.
São Jorge Castle
São Jorge Castle is a historic Moorish-era fortress and popular viewpoint overlooking central Lisbon and the Tagus River.
-
E.
Jerónimos
Jerónimos is an upscale, historic neighborhood in central Madrid known for landmarks like El Retiro Park and the Prado Museum.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (3 batches)
The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.
| Step | Stage | Batch ID | Status | When |
|---|---|---|---|---|
| creating | Elicitation | batch_69a4938db1f081909bcd1ad2713b6096 |
completed | March 1, 2026, 7:29 p.m. |
| NER | Named-entity recognition | batch_69a4acaf30a48190a10ed7fee464c444 |
completed | March 1, 2026, 9:16 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69a826d10188819085413db5a7f6bd11 |
completed | March 4, 2026, 12:34 p.m. |
Created at: March 1, 2026, 7:39 p.m.